Application of Quantum Genetic Optimization of LVQ Neural Network in Smart City Traffic Network Prediction
Autor: | Laiyang Liu, Rui Xiong, Tsu-Yang Wu, Gangyi Ding, Fuquan Zhang, Yiou Wang, Peng Mei |
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Rok vydání: | 2020 |
Předmět: |
LVQ neural network
Learning vector quantization Quantitative Biology::Neurons and Cognition General Computer Science Artificial neural network Computer science global optimization QGA Computer Science::Neural and Evolutionary Computation short-term traffic flow prediction General Engineering computer.software_genre Maxima and minima Traffic flow (computer networking) Smart city Convergence (routing) General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Data mining Cluster analysis lcsh:TK1-9971 computer Global optimization |
Zdroj: | IEEE Access, Vol 8, Pp 104555-104564 (2020) |
ISSN: | 2169-3536 |
DOI: | 10.1109/access.2020.2999608 |
Popis: | Accurate prediction of traffic flow in urban networks is of great significance for smart city management. A short-term traffic flow prediction algorithm of Quantum Genetic Algorithm - Learning Vector Quantization (QGA-LVQ) neural network is proposed to forecast the changes of traffic flow. Different from BP neural network, Learning Vector Quantization (LVQ) neural network is of simple structure, easy implementation and better clustering effect. Utilizing the global optimization ability of Quantum Genetic Algorithm (QGA), it is combined with LVQ neural network to overcome some shortcomings of LVQ neural network, including sensitive to initial weights and prone to local minima. In order to test the convergence ability and the timeliness of QGA-LVQ neural network in short-term traffic flow, some contrast experiments are performed. Experimental simulation results show that, QGA-LVQ neural network obtains excellent prediction results in prediction accuracy and convergence speed. Besides, compared with GA-BP neural network and wavelet neural network, QGA-LVQ neural network performs better in short-term traffic flow prediction. |
Databáze: | OpenAIRE |
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